CognitiveAristocracy
Detail
Overview / Regions / Pittsburgh

Pittsburgh

US Power #73/162Per-capita #26National view: United States →
Metro Power
46.7
of 100 · #73
MPI
46.7
MCC
58.3
MDI
60.1

Pillar profile

Talent56.2
Capital43.0
Research61.5
Infrastructure70.5
Agentic60.1

Indicators

  • Population (m)2.4
  • GDP ($bn)170
  • GDP per capita ($k)72.3
  • AI investment ($bn)6
  • Tech employment %12
  • AI talent74
  • Research strength88
  • Notable AI orgs22
  • Compute / data centers58
  • Broadband %93
  • Tertiary degree %42
  • Digital skills80
  • Startup ecosystem62
  • Agent adoption58
  • Patents / 100k140

Nearest peers

Metro report · generated from Pittsburgh's indicators

Pittsburgh — metro standing in full

Pittsburgh is the #77 metro by economic size ($170bn) in the panel and ranks #73/162 on absolute Metro Power and #26/162 on per-capita intensity. Its strongest pillar is Agentic (60.1, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 58.3 vs CC 86.7).

National context: United States scores CC 86.7 per-capita; Pittsburgh sits at MCC 58.3.

Economic & scale context ● US Census ACS-1 2022 (population); GDP curated

GDP (metro)
$170bn
#77 of 162
GDP / capita
$72k
Population
2.4M
AI investment
$6.0bn
#33 of 162
Notable AI orgs
22

Index & pillar read

For each metro index and pillar: what it means when high (the value) versus low (the gap), and Pittsburgh's own standing.

Index / pillarValueStandingWhat a high vs low value means — and where Pittsburgh sits
MPI Metro Power46.7Moderate · #73/162Mid-pack. High would mean a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem; low would mean limited absolute weight — a smaller node that leans on capacity built in larger hubs.
▲ high: a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem  ·  ▼ low: limited absolute weight — a smaller node that leans on capacity built in larger hubs
MCC Metro Coefficient58.3Strong · #26/162High here — deep capability per resident — a concentrated, high-intensity ecosystem.
▲ high: deep capability per resident — a concentrated, high-intensity ecosystem  ·  ▼ low: thin intensity per resident — capability is sparse relative to the population
MDI Metro Agentic60.1Leading · #16/162High here — agents are widely deployed locally — a near-term productivity multiplier.
▲ high: agents are widely deployed locally — a near-term productivity multiplier  ·  ▼ low: agentic deployment is shallow — the local agent lever is under-used
Talent Talent56.2Strong · #24/162High here — a deep talent pool — the scarcest input to building AI.
▲ high: a deep talent pool — the scarcest input to building AI  ·  ▼ low: a shallow talent base that constrains how much can be built locally
Capital Capital43.0Strong · #40/162High here — abundant capital flowing into building cognitive infrastructure.
▲ high: abundant capital flowing into building cognitive infrastructure  ·  ▼ low: thin investment — good ideas struggle to scale locally
Research Research61.5Strong · #19/162High here — a strong research base feeding a pipeline of ideas and people.
▲ high: a strong research base feeding a pipeline of ideas and people  ·  ▼ low: a weak research base — fewer home-grown breakthroughs and spinouts
Infrastructure Infrastructure70.5Moderate · #58/162Mid-pack. High would mean the physical and digital rails to run AI at scale are in place; low would mean infrastructure gaps cap how much AI can actually be run locally.
▲ high: the physical and digital rails to run AI at scale are in place  ·  ▼ low: infrastructure gaps cap how much AI can actually be run locally
Agentic Agentic60.1Leading · #16/162High here — agents are actively deployed — an early-mover productivity edge.
▲ high: agents are actively deployed — an early-mover productivity edge  ·  ▼ low: little agentic deployment — the near-term lever is unused

Strengths to build on

  • Agentic (60.1, Leading) — agents are actively deployed — an early-mover productivity edge.
  • Research (61.5, Strong) — a strong research base feeding a pipeline of ideas and people.
  • Talent (56.2, Strong) — a deep talent pool — the scarcest input to building AI.

Risk factors

  • No acute structural gaps stand out across the metro pillars.
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.